Systematic Planning for Urban Solid Waste Logistics: A Multi-Stage Decision Model from Routing to Facility Location

Abstract

Urban solid waste management is transitioning, with waste sorting and transportation network optimization being central to enhancing system resilience and efficiency. This study aims to develop a multilevel, multi-objective optimization paradigm to address the complexity of urban waste transportation systems. The research begins with a basic Capacitated Vehicle Routing Problem (CVRP) model designed to minimize the total transportation distance as a benchmark. Based on this, we constructed a comprehensive cost optimization model that incorporates multiple waste categories, heterogeneous vehicles, and spatiotemporal constraints. Ultimately, the framework was elevated to the strategic level by integrating the transfer station facility location and low-carbon route planning, thus forming an integrated “strategic location–tactical allocation–execution route” decision-making model. T used an improved genetic algorithm (IGA) based on an elite retention strategy to solve the model. Empirical analysis shows that the basic model establishes a baseline of 1,049.29 km in total mileage; the multi-constraint collaborative model achieves a multi-objective balance at a daily cost of 4,511.33 yuan; while the integrated model outputs the optimal spatial layout of transfer stations and quantifies that an asymmetric road network leads to increases in transportation cost and carbon emissions by 0.62% and 1.12%, respectively. The hierarchical optimization framework not only provides an end-to-end decision support tool for urban solid waste management but also offers methodological references for solving complex urban logistics network problems.